Site Reliability Optimization Analyst / Lead / Scientist

• Bachelor's degree in computer science, Information Technology, or a related field with specialization in data science (or equivalent experience).

• 5+ years of experience in data analysis or data science, preferably in a technical or engineering environment.
• Telecom domain experience is good to have.

• Proficiency in data analysis tools (e.g., SQL, Python, etc.,).
• Strong understanding of statistical concepts and techniques.
• Experience with data visualization tools (e.g., Tableau, Power BI, kibana, graphana, DOMO).
• Familiarity with cloud-based infrastructure and applications (e.g., AWS, Azure, GCP).
• Ability to work effectively in a fast-paced, collaborative environment.
• Experience working with large datasets, log analysis, and tools like Elastic and Domo (or similar) will be a significant advantage.
• Strong knowledge of AI/ML algorithms and frameworks (e.g., TensorFlow, PyTorch).
• Experience with anomaly detection techniques and tools.

• Advanced degree in data science or a related field.
• Experience in the telecom domain.
• Certification in data science or machine learning.

Key Duties Responsibilities
1 AI/ML Model Development: Develop and implement AI/ML models to analyze system behavior, identify anomalies, and predict potential issues.
2 Collaborative Problem Solving: Work closely with SRE and DevOps teams to identify data logs, analyze system behavior, and develop AI/ML models to address issues.
3 Data Analysis and Modeling: Conduct in-depth analysis of large-scale datasets (SQL, NoSQL) to extract valuable insights and build predictive models.
4 Anomaly Detection: Develop robust anomaly detection algorithms to flag unusual system behavior and prevent potential disruptions.
5 Data-Driven Optimization: Optimize system performance and resource allocation based on data-driven insights and AI/ML recommendations.
6 ML Capability Utilization: Ensure effective integration and utilization of ML capabilities across the SRE team to enhance operational efficiency and reliability.
7 Telemetry Data Analysis: Analyze large datasets of telemetry data from various sources (e.g., call logs, performance metrics, system logs) to identify patterns, trends, and anomalies.
8 Alerting Optimization: Develop and refine alerting rules based on data-driven insights to ensure timely notification of critical issues and minimize alert fatigue.
9 Proactive Issue Identification: Leverage data analysis techniques and AI/ML models to proactively identify potential system issues or outages before they occur.
10 Root Cause Analysis: Investigate and analyze incidents to identify root causes and implement preventive measures.
11 Data Visualization: Create clear and informative visualizations to communicate findings to stakeholders and facilitate decision-making.

Preferred Skills Preferred:
Advanced degree in data science or a related field.
Experience in the telecom domain.
Certification in data science or machine learning. Required Skills 5+ years of experience in data analysis or data science, preferably in a technical or engineering environment.
Telecom domain experience is good to have.